Targeting SARS-CoV-2 main protease by teicoplanin: A mechanistic insight by docking, MM/GBSA and molecular dynamics simulation

Abstract

First emerged in late December 2019, the outbreak of novel severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) pandemic has instigated public-health emergency around the globe. Till date there is no specific therapeutic agent for this disease and hence, the world is craving to identify potential antiviral agents against SARS-CoV-2. The main protease (M^Pro) is considered as an attractive drug target for rational drug design against SARS-CoV-2 as it is known to play a crucial role in the viral replication and transcription. Teicoplanin is a glycopeptide class of antibiotic which is regularly used for treating Gram-positive bacterial infections, has shown potential therapeutic efficacy against SARS-CoV-2 in vitro. Therefore, in this study, a mechanistic insight of intermolecular interactions between teicoplanin and SARS-CoV-2 M^Pro has been scrutinized by molecular docking. Both monomeric and dimeric forms of M^Pro was used in docking involving blind as well as defined binding site based on the known inhibitor. Binding energies of teicoplanin-M^Pro complexes were estimated by Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) computations from docking and simulated trajectories. The dynamic and thermodynamics constraints of docked drug in complex with target proteins under specific physiological conditions was ascertained by all-atom molecular dynamics simulation of 100 ns trajectory. Root mean square deviation and fluctuation of carbon α chain justified the stability of the bound complex in biological environments. The outcomes of current study are supposed to be fruitful in rational design of antiviral drugs against SARS-CoV-2.

Keywords: Covid-19; Docking; Molecular dynamics; SARS-CoV-2 main protease; Teicoplanin.

Graphical abstract

Fig. 1

Chemical structure of the teicoplanin used in present study.

Fig. 2

An outline of the adopted methodology in this study.

Fig. 3

Best docked poses of the teicoplanin (shown as CPK rendering) in both monomeric and dimeric forms of the M^Pro. Teicoplanin docked in monomeric form is represented in dark blue color while dark pink color is used to demonstrate docked teicoplanin in the dimeric protein. Chain A is presented as solid ribbon while chain B has been rendered as line ribbon in cyan color (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).

Fig. 4

Teicoplanin in complex with monomeric M^Pro. A and B shows blind docking results of first and last frame, respectively. C and D depicts defined docking results of first and last frame, respectively. All frames were extracted from 100 ns MD simulated trajectories.

Fig. 5

Teicoplanin in complex with dimeric M^Pro. A and B represents blind docking results of first and last frame, respectively. C and D depicts defined docking findings of first and last frame, respectively. All frames were extracted from 100 ns MD simulated trajectories.

Fig. 6

The root-mean square deviations (RMSD) of Cα atoms of SARS-CoV-2 main protease in apo form (A,B) and in complex with teicoplanin (C-F) during 100 ns MD simulation.

Fig. 7

The root-mean square fluctuation (RMSF) of Cα atoms of SARS-CoV-2 main protease in apo form (A,B) and in complex with teicoplanin (C–F) during 100 ns MD simulation. The point of contact of teicoplanin with protein residues is shown by vertical green lines on X-axis. Loop regions are shown by white bar whereas alpha-helices and beta-sheets are represented in the form of blue and pink bars, respectively (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).

Fig. 8

Radius of gyration (rGyr, shown in Å unit) of numerous complexes of teicoplanin with M^Pro during simulated period of 100 ns.

Fig. 9

Solvent accessible surface area (SASA, depicted in Ų) of numerous complexes of teicoplanin with M^Pro during simulated period of 100 ns.

Fig. 10

Monomeric M^Pro interactions with teicoplanin, monitored throughout the simulation trajectories. These interactions are clustered by type and summarized in bar diagram including H-bonds, hydrophobic, ionic and water bridges.

Fig. 11

Dimeric M^Pro interactions with teicoplanin, monitored throughout the simulation trajectories. These interactions are clustered by type and summarized in bar diagram including H-bonds, hydrophobic, ionic and water bridges.